The present invention generally relates to the field of image reconstruction in computed tomography (CT) systems and more particularly to a method and apparatus for reducing artifacts in image data generated by computed tomography systems.
CT scanners operate by projecting fan shaped or cone shaped X-ray beams through an object. The X-ray beams are generated by an X-ray source, and are generally collimated prior to passing through the object being scanned. The attenuated beams are then detected by a set of detector elements. The detector elements produce a signal based on the intensity of the attenuated X-ray beams, and the signals are processed to produce projections. By using reconstruction techniques, such as filtered backprojection, useful images are formed from these projections.
A computer is able to process and reconstruct images of the portions of the object responsible for the radiation attenuation. As will be appreciated by those skilled in the art, these images are computed by processing a series of angularly displaced projection images. This data is then reconstructed to produce the reconstructed image, which is typically displayed on a cathode ray tube, and may be printed or reproduced on film.
As CT scanners are developed with larger and larger detectors, they begin to encounter problems with artifacts in the reconstructed image that arise due to the cone angle of the scanner. An increase in the cone angle beyond a certain limit can result in a degradation of the image quality produced by the scanner. Another particular problem with reconstructed images in CT systems are artifacts caused by the presence of high density objects, for example, metal objects in a subject. The presence of such high density objects in a subject causes relatively high attenuation of the X-ray beams as they propagate through the subject, thereby resulting in a reconstructed image with artifacts. The artifacts are due to one or more effects such as beam hardening, measurement noise, scatter, partial volume effect, aliasing, object motion and photon starvation.
Many techniques have been employed to reduce artifacts in image reconstructions. Some of these techniques include pre-processing of the sinogram data, modifying the reconstruction algorithm to reduce artifacts, or through post-processing of the reconstructed image. Pre-processing of the sinogram data comprises correcting for physical effects such as beam hardening, partial volume and scatter, or using adaptive filtering or projection completion techniques. Modifying the reconstruction algorithm comprises ignoring measurements through the high density objects, using special image basis functions, incorporating the physics of the acquisition in the reconstructed algorithm, using lower weights for corrupted measurements or including prior information. Post-processing the reconstructed image typically comprises removing artifact streaks using pattern recognition or by applying reformats to avoid and average out the artifacts.
A disadvantage of the above techniques is that they result in either only a partial reduction of artifacts, introduce new artifacts, have a high computation time or result in the formation of blurred images. Therefore, there exists a need in the art for an improved technique for generating image data with reduced artifacts.